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@farzaa
farzaa / wiki-gen-skill.md
Last active April 12, 2026 00:14
personal_wiki_skill.md
name wiki
description Compile personal data (journals, notes, messages, whatever) into a personal knowledge wiki. Ingest any data format, absorb entries into wiki articles, query, cleanup, and expand.
argument-hint ingest | absorb [date-range] | query <question> | cleanup | breakdown | status

Personal Knowledge Wiki

You are a writer compiling a personal knowledge wiki from someone's personal data. Not a filing clerk. A writer. Your job is to read entries, understand what they mean, and write articles that capture understanding. The wiki is a map of a mind.

LLM Wiki

A pattern for building personal knowledge bases using LLMs.

This is an idea file, it is designed to be copy pasted to your own LLM Agent (e.g. OpenAI Codex, Claude Code, OpenCode / Pi, or etc.). Its goal is to communicate the high level idea, but your agent will build out the specifics in collaboration with you.

The core idea

Most people's experience with LLMs and documents looks like RAG: you upload a collection of files, the LLM retrieves relevant chunks at query time, and generates an answer. This works, but the LLM is rediscovering knowledge from scratch on every question. There's no accumulation. Ask a subtle question that requires synthesizing five documents, and the LLM has to find and piece together the relevant fragments every time. Nothing is built up. NotebookLM, ChatGPT file uploads, and most RAG systems work this way.

@BretFisher
BretFisher / Docker Model Runner Reference.excalidraw.png
Last active April 12, 2026 00:09
Use Open WebUI with Docker Model Runner and Compose
Docker Model Runner Reference.excalidraw.png
"""
The most atomic way to train and run inference for a GPT in pure, dependency-free Python.
This file is the complete algorithm.
Everything else is just efficiency.
@karpathy
"""
import os # os.path.exists
import math # math.log, math.exp
https://youtu.be/-C-JoyNuQJs?t=39m45s
When I put the reference implementation onto the website I needed to
put a software license on it.
And I looked at all the licenses that were available, and there were a lot
of them. And I decided that the one I liked the best was the MIT License,
which was a notice that you would put on your source and it would say,
"you're allowed to use this for any purpose you want, just leave the
notice in the source and don't sue me."